Craig Paterson

Craig Paterson

I'm a strategy advisor and coach with specialisms in Business, Data & Digital strategy development and execution. I get my energy from working with smart people to solve relevant challenges.

Location Scotland


  • that's great to hear, good luck on your journey.

  • I like your approach.

  • I think it is seen as too hard to put it on the balance sheet right now (and will put a spotlight on responsibilities that are hard to meet), but as you say, it's an interesting conversation that raises awareness of the understanding of the value of data.

  • it sounds like a win to me too

  • Don't rush into Data Science until you need. You don't want to recruit (and insure the cost of a data scientist) if it is not what you need.

  • Data Teams Models to consider:

    1. Federated - Dedicated data resources are embedded within existing Lines of Business

    2. Centralised - All dedicated data resources within a single team that offers data services to the existing Lines of Business

    3. Centre of Excellence (CoE) - A team that coordinates data services across all of the organisation by...

  • From some other other TDL material: "The attributes and criteria which should be front of mind when planning how to set up and structure a data team include:

    Maximise collaboration – remove silos and encourages working toward shared goals
    Responsive and flexible – provides ability to flex to changing demands
    Clear ownership – removes ambiguity, gaps and...

  • regular engagement and comms are often overlooked in data initiatives

  • most people I have worked with have taken a phased approach

  • thats great to hear

  • as is often said, less is more. My mantra is "what is the minimum, but no less, amount of data I need?"

  • To me, leadership and culture are what will make or break these initiatives.

  • this is a great tool for triggering conversations

  • I within 3s, The top 3 KPIs and 3 supporting KPIs for each.

  • making the compelling case for change is key, as is taking small, "meaningful and achievable " steps. We look at this later in the course.

  • that's great that the process and workbook have been useful

  • good luck

  • indirectly in some cases but not all to share the data with others, often it is services and APIs that become the route to monetisation.

  • another great insight "I think people are generally much more careful with other people’s data than their own."

  • data is definitely a team game, and its the weakest links we need to watch out for

  • great insights, sometime there really isn't a meaningful choice, its all or nothing.

  • @JUMOKEOGUNDARE thank you. I hope your data journey is going well.

  • Overcoming legacy is a challenge. Hopefully later in the course you wills some idea emerge to address this.

  • Thanks for sharing. Do you do anything around predicting student behaviour? I am thinking, can you see when a student it starting to disengage and intervene before it is too late?

  • narrowing down to something that is both meaningful and achievable is key success, and something that we will come to discuss throughout the course

  • the symbiotic relationship is a key point

  • excellent

  • thank you for participating and commenting. Good luck on your data journey.

  • we will coverall of that in the next few weeks

  • @RogerBox, here’s my suggestion. They are all needed for success but this is how I would suggest you start:

    1st focus on Leadership and People, so that you have clarity on accountabilities for making it happen and you have the ability to do the first interesting thing that will engage the organisation.

    2nd focus on Strategy and Skills, so that you know...

  • thank you, that is great to hear. Enjoy your next steps.

  • @HansGNedden thanks for the feedback and the links. We may be developing a Data Science course soon as this one is intended as an introduction to leadership.

  • That's an interesting article. I echo the point that one of the common challenges with recruitment in Data Science is that often people try to recruit someone when they don't need one and/or haven't done the ground work to created the environment for a Data Scientist to be successful.

    We have had lot of conversations with recruitment agencies to help them...

  • @HansGNedden I think you will like this McKinsey article called "Six problem-solving mindsets for very uncertain times".

    It includes this quote "good problem solving typically involves designing experiments to reduce key uncertainties. Each move provides additional information and builds...

  • again, thanks for sharing your views, it is good to get debates going.

    The point we were hoping to make here is that manipulation of data, combining it, generating insights, capturing feedback, learning from it etc all generate new data that creates a more complete and hopefully valuable view. As such, the more you use and combine data, the great value you...

  • Thanks for sharing your views. We included this here to trigger thoughts on people's behaviour when it comes to data , especially ownership and the consequences of not looking after data. This thought exercise, of putting a balance sheet value on data, has worked for many people help them reject and realise that if data was tracked financially, then they...

  • I am really glad that you found it useful.

  • absolutely, we often use the same words but attached different meanings to them.

  • A great insight, thanks for sharing. There is a difference between being right and being useful. One of the things a leader does is help the data people to be more that just right, and to become useful to the business.

  • Fantastic, I am glad you found it useful. Good luck with your data journey.

  • That's a great and really honest answer. Give yourself time to make the right decision for your organisation - it may not all sit-in one role.

  • Thank you, I am glad you found it useful. Enjoy the next steps on your data journey.

  • the Data Lab can help, so feel free to get in touch

    Your insight is spot on, for example, these are questions we come across frequently:

    >> which skills do I need?
    >> what interview questions should I ask?
    >> what does good interview question answer look like?
    >> how much should I pay?

    Skills Development Scotland...

  • indeed, well done :)

  • a great insight, thank you for sharing.

  • This is great, thank you for sharing. One thing to consider is how could you get at best one data insight in front of your Board / Leadership Team / Sponsors / Investor at the next meeting and use that to stimulate a conversation ie does this data feel right? can we improve on this? what is missing? what new questions does this insight raise? how would we...

  • I agree, the two are often interrelated.

  • @CatherineStewart are people's accountability for success clear in the scenario you are referring? If they don't feel accountable for moving on then you run the risk of people enjoying the debate at the expense of making decisions. A good neutral facilitator and an active sponsor can make a big difference in these situations.

  • Focusing on the explicit funding is a good way to sharpen the focus on the conversion regarding what is really a priority. If it is not funded are the stakeholders really committed?

  • this is a great comment and observation. The purpose of strategy is to give clarity, focus investment and give you parameters that allow you to make decisions as to what to do (or not do). Asking the questions we pose in this week will hopefully help you see what your strategy is, or help you identify which questions to ask to clarify what your strategy is.

  • hopefully some of the things we cover in subsequent weeks all help you narrow down what your next step are and make it less overwhelming.

  • hi, the funnelling down was done by the Data Scientist who spend the majority of their time cleaning and quality checking the data then removing information that wasn't linked to the business outcome.

  • It makes perfect sense. Having agreed definitions is critical to success. Sometimes people use the same words with different meanings which can result in the illusion of agreement. A Data Dictionary is a good way to flesh out exactly what everyone means and to agree definitions.

  • a good insight, so don't be too harsh on yourself!

  • New opportunities and ways working are emerging all the times, so to me maturity is about how you keep moving forward. This week we looked at data analytics maturity - how advanced you are in your ability to use data to drive value - and next week we look at organisational maturity - how ready you are to take action based upon the insights...

  • later in the course we look at how to overcome these barriers and we also get more tips from partitioners that will hopefully give you tips and inspiration

  • it maybe worth capturing the "risk of doing nothing" as a way to catalyse a discussion - busyness and "the status quo" are frequently used as a rationale for delaying action

  • in week 4 we look at ways to overcome these barriers so hopefully you will get some new tips and ideas then

  • that's great, we will build on this in later weeks.

  • that's really great to hear

  • that's excellent that you have an initial idea in mind.

  • great, that sounds really exciting

  • @AnnaMacLean later in the course we talk about the value of starting small and growing. Having "meaningful and achievable" first project will keep you focussed and help identify the sub-set of your data to work on first.

  • That is great, thanks for sharing. You are right, this is a good exercise to do with different scopes: where are you? your team? your department? your consumers? your founders? your organisation? etc. as this helps identify disjoints that may benefit from alignment.

    And quite often it is a range, not a specific point, that your score yourself on the...

  • that is great and thanks for sharing. Most people end up realising that have a lot of data so the hard thing is deciding where to start and what to trust. Hopefully the following weeks' activities will help you decide where to start.

  • @LauraCoveney and @JaneGriffin - I also agree, the two are pretty symbiotic and we discuss this later in the course.

  • hi, hopefully the information shared on Aggreko on this course (in the subsequent weeks) will be useful to you.

  • Later in the course we talk about "meaningful and achievable" first steps. Hopefully that material will help you.

  • hi, hopefully what we cover on this course will help you with this. I think the maturity models we cover in weeks 2 and 3 will be useful to frame these conversations.

  • I agree. Cultural change is hard but often happens though "leadership by example".

  • Great insights. Thanks for sharing.

  • Absolutely. It usually takes an independent industry body (or a cohort of influential companies) to get together to agree where to cooperate for the benefits of the industry and where to compete for the benefit of the customer.

  • excellent, it often raises a number of new questions to explore including the dependency on external organisations to create the value and the responsibly of employees to maintain (and enhance) the value.